Application of Neural Networks to Human Genome Sequencing. (Reannouncement withNew Availability Information)

摘要

There is a tremendous amount of existing genome sequence data that is in need ofanalysis, and the database is rapidly growing. Conventional sequential techniques of computer processing are either too slow or not powerful enough to meaningfully analyze this data. Neural network simulation, either in software or hardware, is a promising approach to this problem. The dynamic Hopfield type neural networks were applied to the analysis of genome sequences alignment. Unique energy equations were devised and the weight design for a dynamic network based solution to the genome sequence alignment problem.